Hybrid enhanced particle swarm optimization for VTOL UAV sliding mode controller: A methodological
This paper introduces an improved Sliding Mode Controller (SMC) using Hybrid Enhanced Particle Swarm Optimization (HEPSO) for parameter tuning, optimizing c1, c2, η1, and η2. HEPSO integrates adaptive inertia weights (AIW), unified factor enhancement (UFE), and global optimal particle training (GOPT...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-11-01
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| Series: | Ain Shams Engineering Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2090447925004356 |
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| _version_ | 1849228390557548544 |
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| author | Zhong Wei Liu Si Bo Huang Tian Yu Zhang He Wang |
| author_facet | Zhong Wei Liu Si Bo Huang Tian Yu Zhang He Wang |
| author_sort | Zhong Wei Liu |
| collection | DOAJ |
| description | This paper introduces an improved Sliding Mode Controller (SMC) using Hybrid Enhanced Particle Swarm Optimization (HEPSO) for parameter tuning, optimizing c1, c2, η1, and η2. HEPSO integrates adaptive inertia weights (AIW), unified factor enhancement (UFE), and global optimal particle training (GOPT), enhancing its performance. Validated against CEC2022 benchmark functions, HEPSO excels in convergence and precision over other PSO variants. Its practicality was tested in VTOL UAV simulations, outperforming PSO-SMC, IPSO-SMC, and UPS-SMC, proving its effectiveness in UAV control systems. This study upgrades SMC performance and offers a robust control strategy for UAVs. |
| format | Article |
| id | doaj-art-b50cf5e6ed9f4f1e87ea89a916d9cc1b |
| institution | Kabale University |
| issn | 2090-4479 |
| language | English |
| publishDate | 2025-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ain Shams Engineering Journal |
| spelling | doaj-art-b50cf5e6ed9f4f1e87ea89a916d9cc1b2025-08-23T04:48:00ZengElsevierAin Shams Engineering Journal2090-44792025-11-01161110369410.1016/j.asej.2025.103694Hybrid enhanced particle swarm optimization for VTOL UAV sliding mode controller: A methodologicalZhong Wei Liu0Si Bo Huang1Tian Yu Zhang2He Wang3Mechanical Engineering and Automation, University of Science and Technology Liaoning, Anshan 114051, ChinaMechanical Engineering and Automation, University of Science and Technology Liaoning, Anshan 114051, ChinaMechanical Engineering and Automation, University of Science and Technology Liaoning, Anshan 114051, ChinaCorresponding author.; Mechanical Engineering and Automation, University of Science and Technology Liaoning, Anshan 114051, ChinaThis paper introduces an improved Sliding Mode Controller (SMC) using Hybrid Enhanced Particle Swarm Optimization (HEPSO) for parameter tuning, optimizing c1, c2, η1, and η2. HEPSO integrates adaptive inertia weights (AIW), unified factor enhancement (UFE), and global optimal particle training (GOPT), enhancing its performance. Validated against CEC2022 benchmark functions, HEPSO excels in convergence and precision over other PSO variants. Its practicality was tested in VTOL UAV simulations, outperforming PSO-SMC, IPSO-SMC, and UPS-SMC, proving its effectiveness in UAV control systems. This study upgrades SMC performance and offers a robust control strategy for UAVs.http://www.sciencedirect.com/science/article/pii/S2090447925004356Particle Swarm OptimizationSliding mode controllerCEC2022VTOL UAVParameter tuning |
| spellingShingle | Zhong Wei Liu Si Bo Huang Tian Yu Zhang He Wang Hybrid enhanced particle swarm optimization for VTOL UAV sliding mode controller: A methodological Ain Shams Engineering Journal Particle Swarm Optimization Sliding mode controller CEC2022 VTOL UAV Parameter tuning |
| title | Hybrid enhanced particle swarm optimization for VTOL UAV sliding mode controller: A methodological |
| title_full | Hybrid enhanced particle swarm optimization for VTOL UAV sliding mode controller: A methodological |
| title_fullStr | Hybrid enhanced particle swarm optimization for VTOL UAV sliding mode controller: A methodological |
| title_full_unstemmed | Hybrid enhanced particle swarm optimization for VTOL UAV sliding mode controller: A methodological |
| title_short | Hybrid enhanced particle swarm optimization for VTOL UAV sliding mode controller: A methodological |
| title_sort | hybrid enhanced particle swarm optimization for vtol uav sliding mode controller a methodological |
| topic | Particle Swarm Optimization Sliding mode controller CEC2022 VTOL UAV Parameter tuning |
| url | http://www.sciencedirect.com/science/article/pii/S2090447925004356 |
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